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table-transformer-structure-recognition

Object Detection
Transformers
PyTorch
Safetensors
table-transformer
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9
table-transformer-structure-recognition
File size: 1,469 Bytes 
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{
  "activation_dropout": 0.0,
  "activation_function": "relu",
  "architectures": [
    "TableTransformerForObjectDetection"
  ],
  "attention_dropout": 0.0,
  "auxiliary_loss": false,
  "backbone": "resnet18",
  "bbox_cost": 5,
  "bbox_loss_coefficient": 5,
  "ce_loss_coefficient": 1,
  "class_cost": 1,
  "d_model": 256,
  "decoder_attention_heads": 8,
  "decoder_ffn_dim": 2048,
  "decoder_layerdrop": 0.0,
  "decoder_layers": 6,
  "dice_loss_coefficient": 1,
  "dilation": false,
  "dropout": 0.1,
  "encoder_attention_heads": 8,
  "encoder_ffn_dim": 2048,
  "encoder_layerdrop": 0.0,
  "encoder_layers": 6,
  "eos_coefficient": 0.4,
  "giou_cost": 2,
  "giou_loss_coefficient": 2,
  "id2label": {
    "0": "table",
    "1": "table column",
    "2": "table row",
    "3": "table column header",
    "4": "table projected row header",
    "5": "table spanning cell"
  },
  "init_std": 0.02,
  "init_xavier_std": 1.0,
  "is_encoder_decoder": true,
  "label2id": {
    "table": 0,
    "table column": 1,
    "table column header": 3,
    "table projected row header": 4,
    "table row": 2,
    "table spanning cell": 5
  },
  "mask_loss_coefficient": 1,
  "max_position_embeddings": 1024,
  "model_type": "table-transformer",
  "num_channels": 3,
  "num_hidden_layers": 6,
  "num_queries": 125,
  "position_embedding_type": "sine",
  "scale_embedding": false,
  "torch_dtype": "float32",
  "transformers_version": "4.24.0.dev0",
  "use_pretrained_backbone": true
}